SQL Window Totals and Averages | Dataford Interview Questions

Business Context

Balyasny Asset Management needs a daily view of execution activity across instruments to support portfolio and trading analysis.

Task

Write a PostgreSQL query that joins trade executions to instrument metadata, aggregates filled executions by ticker and trading day, and calculates running and sliding-window metrics.

Requirements

Include only executions with execution_status = 'FILLED'.
Aggregate daily executed quantity and daily notional value by ticker and trade date.
Calculate a cumulative executed quantity and cumulative notional value for each ticker.
Calculate the average daily executed quantity over the current day and preceding 29 calendar days. Use a date-based RANGE window, not a row-count window.
Return results ordered by ticker and trade date.

Schema

trade_executions

Column	Type	Description
execution_idPK	INT	Unique execution identifier
instrument_id	INT	References instruments.instrument_id
executed_at	TIMESTAMPTZ	Execution timestamp
quantity	NUMERIC(18,2)	Executed quantity
execution_price	NUMERIC(18,4)	Execution price
execution_status	VARCHAR(20)	Execution lifecycle status
trader_id	VARCHAR(30)	BAM trader identifier

instruments

Column	Type	Description
instrument_idPK	INT	Unique instrument identifier
ticker	VARCHAR(20)	Instrument ticker
asset_class	VARCHAR(30)	Instrument asset classification

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